MULTINOMIAL LOGISTIC REGRESSION ON FACTORS INFLUENCING MALNUTRITION CASES IN BONE BOLANGO DISTRICT

Muhammad Rizkyanto; Muhammad Rezky Friesta Payu; Amanda Adityaningrum

doi:10.55719/mv.v7i1.1653

Authors

Muhammad Rizkyanto Universitas Negeri Gorontalo
Muhammad Rezky Friesta Payu Universitas Negeri Gorontalo
Amanda Adityaningrum Universitas Negeri Gorontalo https://orcid.org/0000-0002-9874-7641

DOI:

https://doi.org/10.55719/mv.v7i1.1653

Keywords:

Stunting, Wasting, Underweight, Malnutrition, Chi-square, Multinomial Logistic Regression

Abstract

Malnutrition in children under five, including stunting, wasting, and underweight, is a significant public health issue in the Bone Bolango District. This study aims to examine the factors associated with these three categories of malnutrition using the multinomial logistic regression analysis. Data were collected from 150 children under five and analyzed based on gender, birth weight, birth length, history of exclusive breastfeeding, family income, history of infectious diseases, mother's education level, and iron supplement consumption during pregnancy. The correlation analysis revealed that five factors significantly correlate with malnutrition: gender, history of exclusive breastfeeding, family income, mother's education level, and iron supplement consumption during pregnancy. For the category of malnutrition with more than 1 case, compared to the stunting category, the value of Odds Ratio was 6.8 (p-value = 0.000). For the underweight category, when compared to stunting, the Odds Ratio values for gender and mother's education level were 4.0 (p-value = 0.009) and 0.3 (p-value = 0.047), respectively. In the case of wasting, when compared to stunting, the Odds Ratio values for exclusive breastfeeding and iron supplement consumption during pregnancy were 5.9 (p-value = 0.004) and 5.1 (p-value = 0.007), respectively. Moreover, the Hosmer and Lemeshow goodness of fit test indicated that the regression model was suitable (p-value = 0.126).

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